Signage Research Articles

The Chinese “Streetscape” Investigations on the performative destiny of a social and linguistic space


 
 
 In Europe the street is traditionally the place of self-representation: the “Strada Nuova” in Genova has been designed in 1550 to allow noble families to build their own palaces in a competition of beauty, richness and power. In the American tradition the street became overall a place dominated by its market role (Venturi on Las Vegas, 1972). In China streets are the real public space for people’s daily life and its essential activities (trading, eating, playing, discussing): their role in urban life is so strong that sometime a street can appear even where the planning didn’t establish that.
 The western main urban public/social space is the square, but for the eastern countries - especially China- the streets represent the most representative urban public space that can be used together without the class differences.However, from the ancient cities to today’s high-density cities, the Chinese streets, because of their social role, have experienced also a very important connection with shop signs, posters, notices of all kinds, flags and signs, luminous writings. All these objects are a kind of ornament of daily-life as well as a real interesting documentary material, useful to understand permanencies and variations in the use of the cities during their transition from the former order to the new one.
 The paper introduces the framework and the contents of a multidisciplinary research project at work, between urban morphology and Chinese language and culture. (max. 1500 characters, spaces included)
 
 

Assessing the color status and daylight chromaticity of road signs through machine learning approaches

The color of road signs is a critical aspect of road safety, as it helps drivers quickly and accurately identify and respond to these signs. Properly colored road signs improve visibility during the day and make it easier for drivers to make informed decisions while driving. In order to ensure the safety and efficiency of road traffic, it is essential to maintain the appropriate color level of road signs.The objective of this study was to analyze the color status and daylight chromaticity of in-use road signs using supervised machine learning models, and to explore the correlation between road sign's age and daylight chromaticity. Three algorithms were employed: Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN). The data used in this study was collected from road signs that were in-use on roads in Sweden.The study employed classification models to assess the color status (accepted or rejected) of the road signs based on minimum acceptable color levels according to standards, and regression models to predict the daylight chromaticity values. The correlation between road sign's age and daylight chromaticity was explored through regression analysis. Daylight chromaticity describes the color quality of road signs in daylight, that is expressed in terms of X and Y chromaticity coordinates.The study revealed a linear relationship between the road sign's age and daylight chromaticity for blue, green, red, and white sheeting, but not for yellow. The lifespan of red signs was estimated to be around 12 years, much shorter than the estimated lifespans of yellow, green, blue, and white sheeting, which are 35, 42, 45, and 75 years, respectively.The supervised machine learning models successfully assessed the color status of the road signs and predicted the daylight chromaticity values using the three algorithms. The results of this study showed that the ANN classification and ANN regression models achieved high accuracy of 81% and R2 of 97%, respectively. The RF and SVM models also performed well, with accuracy values of 74% and 79% and R2 ranging from 59% to 92%. The findings demonstrate the potential of machine learning to effectively predict the status and daylight chromaticity of road signs and their impact on road safety in the Swedish context.

Traffic Sign Board Recognition and Voice Alert System using Convolutional Neural Network

Abstract—To ensure a smooth and secure flow of traffic, road signs are essential. A major cause of road accidents is negligence in viewing the Traffic signboards and interpreting them incorrectly. The proposed system helps in recognizing the Traffic sign and sending a voice alert through the speaker to the driver so that he/ she may take necessary decisions. The proposed system is trained using Convolutional Neural Network (CNN) which helps in traffic sign image recognition and classification. A set of classes are defined and trained on a particular dataset to make it more accurate. The German Traffic Sign Benchmarks Dataset was used, which contains approximately 43 categories and 51,900 images of traffic signs. The accuracy of the execution is about 98.52 percent. Following the detection of the sign by the system, a voice alert is sent through the speaker which notifies the driver. The proposed system also contains a section where the vehicle driver is alerted about the traffic signs in the near proximity which helps them to be aware of what rules to follow on the route. The aim of this system is to ensure the safety of the vehicle's driver, passengers, and pedestrians. Keywords—Convolutional Neural Network, GTSRB Dataset, Object Detection, Object Classification Traffic, Traffic Signs, Voice Alert

Student perception and performance with self‐guided learning in soil science laboratory courses

AbstractDuring the COVID‐19 pandemic, preexisting soil science laboratories were redesigned for self‐guided learning (SGL). The SGL laboratories occurred on‐campus during the fall 2020 semester in two introductory soil science courses at the University of Tennessee at Martin and Virginia Polytechnic Institute and State University. Students carried out the activities by visiting multiple outdoor sites on campus, individually or in pairs, without the instructor. Students accomplished this by following instructions provided on location sign boards and instruction manuals. We evaluated student perceptions of the SGL laboratories using an optional qualitative survey that students completed post‐laboratory and student performance on SGL activities using rubrics. Our results showed that students found the difficulty level and amount of time required for the SGL laboratories to be equal to traditional in‐person laboratories. Most students found the SGL laboratories enjoyable or very enjoyable because of the flexibility and hands‐on learning outdoors. Students recommended more SGL laboratories during and after the pandemic, preferably accompanied by frequent student–instructor interaction. Rubric analysis showed that SGLs were best suited for practicing previously learned skills in practical contexts and learning simple skills and concepts, but students did not perform well with complex and abstract concepts. Overall, students were able to successfully complete SGL laboratory activities in a hands‐on yet socially distanced way. The results suggest that SGLs can be implemented in post‐pandemic lectures and laboratory courses designed for hands‐on learning in a distance learning format.

Distance Measuring of Traffic Sign Boards Using Machine Learning

Distance Measuring of Traffic Sign Boards Using Machine Learning

“Dream Boy” and “Hotmale”

Abstract Gender and sexuality have gradually become the focus of more semiotic landscape research, however, studies relating specifically to sex tourism spaces are limited and with those in the Thai context even more so. Therefore, this paper examines the discursive construction of Phatphong 2, one of the famous destinations for sex tourism in Bangkok among male homosexuals, as queer space. Drawing on code preference and inscription (Scollon and Scollon 2003) and visual social semiotics (Kress and Van Leeuwen 1996), we analyze the linguistic and semiotic resources in sexed signs. Findings reveal that Englishization, particularly the terms “boy” and “Bangkok” in shop signs, creates a glocalized and international queer identity for Phatphong 2. The salience of the lean male muscular body and marginalization of transwomen in promotional signs unveil the hegemonic masculinity in queer sex tourism spaces. The study concludes that sexed signs in sex tourism spaces are semiotic aggregates of global queer culture.

A Scoping Review on The Use of Extracorporeal Cardiopulmonary Resuscitation for Refractory Out-Of-Hospital Cardiac Arrest

Aim of the review: To provide an overview of studies that have published data regarding region and population size, procedure location, team composition, inclusion and exclusion criteria, outcome parameters, and cost–benefit analyses on extracorporeal membrane oxygenation use for refractory out-of-hospital cardiac arrest. Data sources: A structured systematic literature search of articles published prior to April 27, 2021, was performed in online databases (PubMed, EMBASE, ClinicalTrials.gov, the EU Clinical Trials Register, and Cochrane Library). Results: Sixty-three articles were included based on predefined eligibility criteria. The included articles were published between 2011 and 2021, with the highest number of articles in 2020 and 2021 (50%). Of the 58 articles that reported data on organisational topics, 47 reported transporting the patients to the hospital for cannulation, 10 reported initiating extracorporeal cardiopulmonary resuscitation (ECPR) on-scene, and one reported doing both. The most common inclusion criterion was a lower age limit of 18 years (in 86% of the articles). Other inclusion criteria were witnessed collapse (67%) and initial ventricular fibrillation/tachycardia (43%), asystole (3%), pulseless electrical activity (5%), pulmonary embolism (2%), and signs of life during CPR (5%). The most common exclusion criterion was a do-not-resuscitate order (38%). Of the 44 studies reporting outcomes, 77% reported survival to hospital discharge and 50%, a cerebral performance category score of 1-2. Other outcome parameters were sparsely reported. Conclusion: There is a variation in regional size, team composition, inclusion and exclusion criteria and reported outcomes. These discrepancies make it challenging to determine how to effectively use ECPR.

Linguistic Landscape of Bilingual Shop Signs in Abha, Saudi Arabia

Linguistic Landscape of Bilingual Shop Signs in Abha, Saudi Arabia

Study on Abnormality Sign Detection Method of Photovoltaic Power Generation System using Frequency Difference Distribution Index in Power Generation Region

This paper proposes a new method for detecting electrical abnormal signs of photovoltaic module only by measuring the voltage value and current value, which are the power generation output values on the DC side in a photovoltaic power generation system. The proposed method is an abnormal sign detection method for photovoltaic power generation systems that uses the frequency difference distribution index of power generation output in the power generation region for evaluation. This paper first outlines the proposed power generation region as an evaluation window in the anomaly detection method. Next, as an example of an anomaly sign detection method using the proposed power generation region, we show the effectiveness of a quantitative evaluation using a frequency difference distribution index focusing on the occurrence of measured values in the power generation region. Finally, the validity and effectiveness of the proposed method is demonstrated using measured data from actual mega solar data.

Linguistic landscape in Malaysia: The case of language choice used in signboards

This study aimed to investigate the languages used in shop signs in three different areas in Semenyih, Selangor, Malaysia. Using a mixed-method approach, this paper identified the preferred language for shop signs in the town of Semenyih, Pelangi Semenyih, and Setia Ecohill, as well as examined the relationship between the language choice in signages and linguistic landscape in Malaysia. A total of 180 signboards was photographed to ensure the impartiality of data collection, and they were coded based on four aspects: full names of the shops in various languages, the business scope of the shops, the number of languages used in shop signs, size of the scripts, and layout of languages highlighted, adopted from the study of Shang and Guo (2017). Questionnaires and interviews with the shop owners were also employed to elicit information about their preferences regarding the language choice for their shop signages, which shed light on the impact of the development in Semenyih towards the choice of shop signages. The findings revealed that, despite the regulations imposed by the local city council (Majlis Perbandaran Kajang (MPKJ) or Kajang Municipal Town Council) on the permissible shop signages, the shop owners still used languages other than the Malay language in their signboards, such as English, Mandarin, and Tamil, with English being the most dominant one. This indicates that, as the towns develop, the linguistic landscape here changes with importance being given to signboards in English compared to Malay.

ETHICAL PRACTICES OF DENTISTS IN PUNE CITY: A CROSS SECTIONAL STUDY

Introduction: Every professional body has its own code of conduct for its members. Dental profession in India is regulated by the Dental Council of India (DCI) under the aegis of the Ministry of Health and Family Welfare, Government of India. DCI; a statutory body formed by an act of parliament- the Dentists Act, 1948 (XVI of 1948). Crowding of dentists across cities leads to unhealthy competition and commercialization. This leads to violating the code of conduct put forth by the state dental councils and many of the norms are openly flouted and rules randomly bent. The objective of the present study is to access the amount of violation of the code of conduct by the dental clinics with respect to the clinic name board and advertisement, in and around Pune city, by an on-site survey. Materials and methods-Ethical clearance was obtained from the Ethics Committee of M.C.E society, Azam Campus, Pune. The study consisted of questions regarding the size of the dental clinic board, attractive symbols or wordings, qualifications other than the academic ones, and advertisements of the clinics through media or sign boards. In all, 123 clinics were observed. Statistical analysis was carried out using SPSS 22.0 (Chicago, U.S.A). Results-There were in all 123 clinics (60- BDS and 63- MDS). More BDS practitioners faulted the regulations with respect to size of the sign board, slogans on the board- like “family dentists”, “tooth designing”; fixing the sign board far away from the place of practice- at the pharmacist. Higher percentage of MDS practitioners advertised through media for promoting their clinics compared to the BDS practitioners. Overall more than half of the dentists mentioned their place of study and the university from where they obtained their degrees. Almost 25% mentioned that they had obtained gold medal in their academics and a few of them also specified the subject in which they won the medals. Conclusion: The current study highlights the violation of codes by dentists in Pune city. It also shows that post graduates are also violating norms. It is up to the DCI, to take appropriate steps including the earliest revision of its norms and its supervision of its strict adherence.

Safety sign comprehension of fiberboard industry employees

Safety signs are very important communication tools for accident prevention, fire safety, health hazard information, and emergency evacuation. They are helpful when properly designed and understood by employees. The purpose of the present study was to investigate fiberboard industry employees' understanding of safety signs. 139 participants were asked to indicate the meaning of a series of 22 commonly used safety signs. The mean comprehension score for 22 signs was 66.6% (min. 22.5% and max. 98.6%). The mean score for warning signs was the lowest, prohibition signs was the highest. Poor comprehension score (less than 40%) was noted for the toxic material, automated external heart defibrillator, overhead obstacle, and disconnect mains plug from electrical outlet signs. These low comprehension scores indicate that some symbols may not effectively convey the message to the audience. Safety practitioners and trainers should pay more attention to teach the actual meaning of those signs.

Phonological Account of English Loanwords Adapted by Qunfudhah Arabic Dialect Speakers (QAD)

The current study aimed to investigate, descriptively, how English loanwords become part of Qunfudhah Arabic Dialect (QAD), an Arabic dialect spoken in the southern part of Saudi Arabia. Hundreds of English loanwords were collected using different resources such as social media posts, news articles, blogs, every-day interactions, and shop signs. The purpose was to find out the triggering motive used by QAD speakers to adapt English loanwords. In other words, the paper sought to answer this question: what phonological rules do the QAD speakers implement to adapt the English loanwords? Using the descriptive data analysis method, the results revealed that English loanwords have been phonologically adapted to fit into the host system using a number of processes to map English consonants and vowels into the recipient language. QAD speakers exercised several modifications to produce an Arabic sound on the foreign consonants (English in this situation) by targeting the manner, place, and voicing. Vowels, on the other hand, were mapped according to the height, tensity, or backness using a number of rules such as monophthongization, lengthening, or position shift. All these processes were used by QAD speakers to more easily produce the foreign sounds, especially those sounds which differ from their own system (marked ones). The result of the current study should add more insights into the body of the literature and pave the way for researchers to investigate this Arabic dialect thoroughly.

ELEMEN LOKAL PADA PAPAN NAMA RESTOAN WARALABA JEPANG DI DENPASAR: KAJIAN LINGUISTIK LANSKAP

The emergence of Japanese restaurants in Indonesia, including franchise networks, companies with foreign and domestic capital, demonstrates that Japanese food is being globalized. Globalization makes it easier for outside culture to infiltrate local life. Events in other worlds can easily be imitated by other parts, resulting in homogeneity in every community's life. Local elements must emerge as markers or characteristics of a specific area as homogeneity is strengthened. Glocalization is the concept of combining global and local cultures. Cultures from outside are then adapted to local culture, resulting in hybridity or unification of the local and the global. Two levels of analysis will be used in researching the glocalization of Japanese franchise restaurant sign boards in Denpasar: the language code type stage and the psychological stage. A descriptive qualitative research method was employed. According to the findings of the analysis, the process of glocalization on the nameplates of Japanese franchise restaurants in Indonesia is carried out by 'transliterating,' or changing the writing from Japanese to Latin letters. Some restaurants include words or sentences that help locals identify the restaurant's characteristics. Regardless, glocalization is done to attract Indonesian consumers.

Character recognition competition for street view shop signs.

This paper presents the inaugural character recognition competition for street view shop signs, including the associated tasks, datasets, participating teams, the winning team's solution, and justification for the award.

Traffic Sign Detection

Abstract: Traffic signs are important to ensure smooth traffic flow without bottle necks or mishaps. Road Symbols are the pictorial representation having different necessary information required to be understood by driver. Road signs in front of the vehicle are ignored by the drivers and this can lead to catastrophic accidents. This paper presents an overview of the traffic sign board detection and recognition and implements a procedure to extract the road sign from a natural complex image, processes it and it alerts the driver using text or voice command. It is implemented in such a way that it acts as a boon to drivers to make easy decisions.

Traffic Sign Detection using Convolutional Neural Networks

Abstract: Signs on the road are crucial making sure the flow of traffic is smooth. Disregard whilst watching the traffic sign board is one of the main causes of traffic accidents. Traffic signs are essential for controlling traffic, preventing accidents, and assuring safety.No entry, speed limit, traffic lights, left or right turn, children crossing, etc. are just a few examples of various sorts of signs. The human observation of traffic control signals under the current approaches could lead to a re-entry collision of cars. The fast-moving traffic may be delayed as a result. Additionally, they impede traffic by stopping cars at the intersection during rush hour. The revised approach uses Deep Learning to reduce the amount of time and effort required to monitor these

Road Sign Board Direction and Location Extraction and Recognition for Autonomous Vehicle.

Road Sign Board Direction and Location Extraction and Recognition for Autonomous Vehicle.

Traffic Sign Board Detection and Voice Alert System

Automated tasks have simplified practically everything we perform in today's world. Drivers often miss signage on the side of the road in an effort to focus on the road, which can be dangerous for them and others. This issue may be avoided if there was a quick way to alert the driver without requiring them to divert their attention. TSDR (Traffic Sign Detection and Recognition) is useful in this situation because it detects and recognizes signs, alerting the motorist to any forthcoming signs. This not only assures road safety, but also puts the driver at ease when driving on unfamiliar or difficult roads. Another issue that arises frequently is the inability to comprehend the sign's meaning. Drivers will no longer struggle to grasp what the sign is saying thanks to this Advanced Driver Assistance Systems (ADAS) application. In this paper, we propose a method for detecting and recognizing traffic signs that uses image processing for detection and an ensemble of Convolutional Neural Networks (LeNet) for recognition. Because LeNet CNN have a high recognition rate, they are ideal for a variety of computer vision tasks. For the CNN implementation, Tensor Flow is employed. And here for object detection we implement yolo frame work On the German data sets, we achieved recognition accuracies of more than 99 percent for circular signs.

Line-of-sight and non-line-of-sight vehicle-to-vehicle communication using light fidelity

Subject of study. Light fidelity is an alluring complementary communication technology for vehicular applications such as vehicle-to-vehicle and navigation systems. The street light communication system can be utilized for sending data like location, sign boards, traffic ahead, emergencies, speed limit, etc. This can help in easy navigation and reduce traffic congestion. Method. In this paper, a hardware model for vehicle-to-vehicle bidirectional communication along with street-light-to-vehicle communication has been presented. A taillight red color light emitting diode with a headlight white color light emitting diode was employed in the experiment to analyze the range in different situations. Main results. This paper also consists of the simulation of a non-line-of-sight communication channel considering different atmospheric conditions. This is effective in cases where line-of-sight communication is not possible. It has been observed that the Q-factors of the signals were 29.53 and 25.80 in the cases of climatic conditions such as clear and heavy fog, respectively. Practical significance. The transmission distance can be increased using brighter lights like used in real life headlights of cars and better photodiodes with higher photosensitivity and fast response time. The proposed prototype is useful in the case of traffic jams and other traffic scenarios.